0558058 20230316105112.120220608235959.9 12 s. P cav_un_epca*0558134978-80-7378-460-71-12PragueMatfyzPress2022StudenýMilanAyNihatColettiGiulianellaKleiterGernot D.ShenoyPrakash P. Decision-Making Uncertainty Industry 4.0 cav_un_auth*0414171 Ahmed U. IT cav_un_auth*0398866 Carpitella Silvia UTIA-B Matematická teorie rozhodování Department of Decision Making Theory MTR MTR IT Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0399068 Certa A. IT http://library.utia.cas.cz/separaty/2022/MTR/carpitella-0558058.pdf Decision-making involves our daily life at any level, something that entails uncertainty and potential occurrence of risks of varied nature. When dealing with industrial engineering systems, effective decisions are fundamental in terms of maintenance planning and implementation. Specifically, several forms of uncertainty may affect decision-making procedures, for which adopting suitable techniques seems to be a good strategy to attain the main maintenance goals by taking into account system criticality along with decision-maker(s) opinions. A wide variety of factors contributes to uncertainty, being some of them greatly important while other ones less significant. However, all of these factors in synergy can impact the functioning of systems in a positive, neutral, or negative way. In this case, the question is whether obtaining a complete picture of such uncertainty can improve decision-making capabilities and mitigate both through-life costs and unforeseen problems. The fundamental issues include dealing with ambiguity in the maintenance decision-making process by employing numerous evaluation criteria and dealing with real-world scenarios in the maintenance environment. In this study, the Multi-Criteria Decision-Making (MCDM) approach is analysed, with particular reference to the Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (FTOPSIS), technique capable to effectively rank alternatives while dealing with uncertainty for maintenance decision-making. A final case study is developed to demonstrate the applicability of the method to the field of maintenance in industry 4.0. The proposed study may be useful in supporting intelligent and efficient decisions resulting in favorable maintenance outcomes. cav_un_auth*0431432 WUPES 2022: 12th Workshop on Uncertainty Processing 20220601 20220604 Kutná Hora CZ AE 20000 20200 20205 2023 3 PR RVO:67985556 http://hdl.handle.net/11104/0332287 S 2022 SCOPUS PUBMED WOS cav_un_epca*0558134 Proceedings of the 12th Workshop on Uncertainty Processing MatfyzPress 2022 Prague 1 12 978-80-7378-460-7 Studený Milan 340 Ay Nihat 340 Coletti Giulianella 340 Kleiter Gernot D. 340 Shenoy Prakash P. 340